“Fitness Fingerprints” Mediate Physiological Culling of Unwanted Neurons in Drosophila

BACKGROUND: The flower gene has been previously linked to the elimination of slow dividing epithelial cells during development in a process known as "cell competition." During cell competition, different isoforms of the Flower protein are displayed at the cell membrane and reveal the reduced fitness of slow proliferating cells, which are therefore recognized, eliminated, and replaced by their normally dividing neighbors. This mechanism acts as a "cell quality" control in proliferating tissues. RESULTS: Here, we use the Drosophila eye as a model to study how unwanted neurons are culled during retina development and find that flower is required and sufficient for the recognition and elimination of supernumerary postmitotic neurons, contained within incomplete ommatidia units. This constitutes the first description of the "Flower Code" functioning as a cell selection mechanism in postmitotic cells and is also the first report of a physiological role for this cell quality control machinery. CONCLUSIONS: Our results show that the "Flower Code" is a general system to reveal cell fitness and that it may play similar roles in creating optimal neural networks in higher organisms. The Flower Code seems to be a more general mechanism for cell monitoring and selection than previously recognized.

Code-specific learning rules improve action selection by populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Cichlid Fish Diversity Threatened by Eutrophication That Curbs Sexual Selection

Cichlid fish species of Lake Victoria can interbreed without loss of fertility but are sexually isolated by mate choice. Mate choice is determined on the basis of coloration, and strong assortative mating can quickly lead to sexual isolation of color morphs. Dull fish col- oration, few color morphs, and low species diversity are found in areas that have become turbid as a result of recent eutrophication. By constraining color vision, turbidity interferes with mate choice, relaxes sexual selection, and blocks the mechanism of reproductive isolation. In this way, human activities that increase turbidity destroy both the mechanism of diversification and that which maintains diversity.

Looking too Old? How First Impressions of Older-looking Candidates Contribute to Unfavorable Selection Decisions

Building on theories of impression formation based on faces, this research investigates the impact of job candidates’ facial age appearance on hiring as well as the underlying mechanism. In an experiment, participants decided whether to hire a fictitious candidate aged 50 years, 30 years or without age information. The candidate’s age was signaled either via chronological information (varied by date of birth) or via facial age appearance (varied by a photograph on the résumé). Findings showed that candidates with older-appearing faces—but not chronologically older candidates—triggered impressions of low health and fitness, compared to younger-appearing candidates. These impressions reduced perceptions of person-job fit, which lowered hiring probabilities for older-appearing candidates. These findings provide the first evidence that trait impressions from faces are a determinant of age discrimination in personnel selection. They call for an extension of current models of age discrimination by integrating the effects of face-based trait impressions, particularly with respect to health and fitness.